Discussion
In this comprehensive analysis of CF NBS algorithms in the USA, we found substantial variations in IRT cutoffs and CFTR variant analysis. These results have important clinical implications for the effectiveness of different states’ CF NBS programs in identifying newborns with CF, and they provide compelling evidence of the need for a nationwide QI effort to make CF NBS more consistent across the country and aligned with best practices.
Although the Centers for Disease Control and Prevention and the Association of Public Health Laboratories (APHL) are two federally-supported organizations with national responsibilities for NBS, they have never shared regional NBS methodologies and outcomes. The only other study that presented data on state CF NBS algorithms was published by Pique, et al in 2015[12]. However, data for that study was acquired at a time when many states were using a CFTR variant analysis kit (Hologic, Marlborough, MA) that was subsequently withdrawn from the market due to manufacturing defects. Furthermore, at the time of their study, many states had not yet progressed to a DNA-based algorithm. Our study presents comprehensive, up-to-date data on CF NBS in the USA at a time when all states are using IRT/DNA algorithms.
Our results have important implications for equity in CF NBS. For example, the two states analyzing only for F508del in the high IRT specimens cannot exceed 85% sensitivity in a typical population of racially and ethnically diverse American infants, However, it has been known for decades[11, 13] that African American and Hispanic infants have variants other than those in commonly used CFTR panels. In fact, the American College of Medical Genetics[14, 15] variant lists were developed primarily for the white population. Although some biotechnology companies have expanded their CFTR panel kits to provide broader racial and ethnic coverage, even with the use of larger CFTR variant panels, e.g. 139 variants, more infants from racial and minority groups will be missed compared to white infants (M McGarry, unpublished observations). Ultimately CFTR sequencing methods[16, 17] are needed to better address the equity challenges.
Our results show that an infant’s probability of being diagnosed early through CF NBS depends on where the birth occurs and also potentially on when a baby is born, i.e., the season of the year. These differences are attributable to both the DNA/CFTR tier and IRT cutoff values and whether they are fixed or floating. Assessment of IRT has demonstrated conclusively that it is a heat-labile biomarker[3, 7] that is also affected by kit-related variations[3, 18]. Every state now shows ambient temperature swings that are being increased by climate change. Although the impact of high temperatures in lowering IRT levels can potentially be mitigated by expedited courier delivery of NBS specimens, the kit-to-kit variations persist. In fact, IRT levels as low as 40 ng/ml have been recorded in states with a 95thpercentile cutoff value [3]. As Martiniano et al reported from analysis of 14 years of monthly IRT data, these variations have been evident since at least 2006 and IRT levels show a downward drift in recent years [18]. That study also revealed the clinical impact of IRT levels slightly below fixed IRT cutoff values as they cause false negative results and “missed cases.” Consequently, while our survey was underway, Colorado, after critically reviewing a large database of over 800,000 babies screened, changed from a fixed threshold at 60 ng/ml to a floating cutoff at the 96th percentile. This is an example of the type of large database driven QI effort needed in many states to reduce the number of false negative results rather than relying on short term, small data sets for evaluations and cutoff conclusions—the apparent modus operandi of most states. Our results demonstrate that many states are not utilizing the optimal method of determining IRT cutoff by continuing to use fixed cutoffs.
It should be emphasized that none of the NBS tests for other genetic conditions show such great variation in cutoff values. Even though the tests used in screening for congenital hypothyroidism have shown seasonal and kit-related variations[19], their impact has apparently not altered sensitivity but does lower the positive predictive value in colder months. The issue of fixed and floating cutoffs has been described in detail in a document published by APHL[20]. In a section on CF, it is stated that “The IRT cutoff is floating and/or fixed. A floating cutoff is recommended because IRT is subject to seasonal variations and lot-to-lot variability of the reagents.” In addition to a higher likelihood of achieving equity, the floating cutoff provides the advantage of a predictable number of samples for DNA/CFTR analyses in the second tier.
It has become increasingly clear that the various CF NBS algorithms are not equivalent in sensitivity and efficiency/timeliness. False negative results are more likely with higher IRT cutoff values[3, 18] and fewer CFTR variants[12]. This raises the question of how such wide variations in CF NBS algorithms arose. A review of the historical evolution of CF NBS tests provides possible answers. In the case ofCFTR variant analysis, the likely explanation is that DNA biotechnology has evolved faster than NBS labs have been able to keep up with opportunities to expand their panels, while adding costs as the new options were marketed in association with greater knowledge ofCFTR pathogenic variants of CF patients[10, 21].
As for the variations in IRT cutoff values, and whether they are fixed or floating, it seems likely that the answer also lies in an historical perspective. Originally, before the discovery of the CFTR gene in 1989, all CF NBS algorithms were IRT/IRT and required what we now regard as relatively high cutoff values to ensure that screening was practical. The CFF raised questions about this and other aspects of IRT-based screening in an influential 1983 position paper[22]. However even after the IRT/DNA or IRT/IRT/DNA algorithms were implemented, the 2-sample states continued with fixed cutoffs through 2020 with the exceptions of Texas and more recently Colorado.
The limitations of this study include our focus on a narrow window of time, i.e., the second half of 2021, during a period in which algorithm changes were occurring. For example, we learned during the analysis of data that Oregon is changing to a floating IRT cutoff and the following states are transforming to next generation sequencing: Florida, Kentucky, and Utah. CF NBS algorithms are constantly changing in every state, and it is likely that regular surveys like our will need to be conducted in order to maintain accurate and current information on CF NBS practices in the USA. In addition, on a national basis we only evaluated the initial IRT cutoff value in the 2-specimen states that employ IRT/IRT/DNA. However, very little research has been done on the optimal IRT cutoff value for the second specimen, and this can be a source of false negative results also[23].
The wide variations in CF NBS algorithms are unique among newborn screening protocols, and involve both IRT cutoffs and CFTR variant analysis. The only consistency is that all states now use a 2-tier strategy beginning with IRT and then, if it is out-of-range, progressing to CFTR variant analysis. Although CF NBS has been offered in the USA now for over a decade, our results demonstrate the need for continued improvement and modification of CF NBS algorithms in order to optimize detection of CF newborns and achieve equity and inclusion in CF NBS.